I made a mobile app and game where you workout to level up

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Hi, I’ve been working on a workout logging mobile app and game to motivate myself to workout called Fittest Fire. Logging workouts in the mobile app gives you points which are used in the game to increase damage, health, speed, etc. The mobile apps are native Kotlin / Swift and have been released. The game is currently in demo status but has the level up system in place. You can easily skip the account creation process for the mobile apps and play around with it first. In that case, you can only save exercises locally. If you have an account, you can save exercises online and get points. Everything is currently free to try (as in beer) Android App: https://play.google.com/store/apps/details?id=com.davesproje... iOS App: https://apps.apple.com/us/app/fittest-fire/id6475898710 Game Steam: https://store.steampowered.com/app/2537510/Fittest_Fire/ Game Itch: https://dtmcderm.itch.io/fittest-fire I appreciate any feedback

Visit product View on Hacker NewsJan 28, 2024

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81%81% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

best fitHighest predicted score across all platforms for this description.

TrustMRRFits verified-revenue profile · Strong signals: mobile apps, ios, apps · Missing: personal, entrepreneurs, video

64%64% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

AppSumoMay struggle as an AppSumo deal · Missing: plus, platform, intuitive

38%38% predicted probability of success on AppSumo, based on ML models trained on real launch data.

Hacker NewsMay not resonate with HN audience · Strong signals: io · Missing: https docs, excited, just released

35%35% predicted probability of success on Hacker News, based on ML models trained on real launch data.

nativeThis product was originally launched on this platform.

Product HuntUnlikely to reach the leaderboard · Strong signals: apple, google, apps · Missing: mac, agents, macos

27%27% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

Acquire.comPre-revenue stage for this audience · Missing: arr, mrr, revenue

19%19% predicted probability of success on Acquire.com, based on ML models trained on real launch data.

BetaListMay not resonate with beta-testers · Missing: web3, chat, crypto

0%0% predicted probability of success on BetaList, based on ML models trained on real launch data.

Incorrect prediction on native model

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